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Modelling an environmentally-extended inventory routing problem with demand uncertainty and a heterogeneous fleet under carbon control policies

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  • Micheli, Guido J.L.
  • Mantella, Fabio

Abstract

Carbon emissions produced by supply chain activities, and in particular by transportation, contribute substantially to global warming. In order to tackle this problem, many governments and regulatory authorities have started to implement carbon control policies, which may directly impact on the decisions of a company. In a traditional inventory routing problem, a supplier determines the optimal vehicle routing and scheduling of deliveries, based on the observed inventory levels of the customers, to minimise the costs of the entire system. This research contributes by modelling the problem simultaneously taking into account the uncertainty in customer demand, a comprehensive emissions model, and a heterogeneous fleet of vehicles. The proposed model is further deployed to address four different policies, namely the cap, the carbon tax, the cap-and-trade and the cap-and-offset. Based on a case study, the economic and environmental implications of each different policy are discussed, focusing on the operational decisions of the models.

Suggested Citation

  • Micheli, Guido J.L. & Mantella, Fabio, 2018. "Modelling an environmentally-extended inventory routing problem with demand uncertainty and a heterogeneous fleet under carbon control policies," International Journal of Production Economics, Elsevier, vol. 204(C), pages 316-327.
  • Handle: RePEc:eee:proeco:v:204:y:2018:i:c:p:316-327
    DOI: 10.1016/j.ijpe.2018.08.018
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    3. Cong Wang & Zhongxiu Peng & Xijun Xu, 2021. "A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies," Mathematics, MDPI, vol. 9(18), pages 1-34, September.
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    6. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    7. Essam Kaoud & Mohammad A. M. Abdel-Aal & Tatsuhiko Sakaguchi & Naoki Uchiyama, 2022. "Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    8. Kumar, Anil & Luthra, Sunil & Mangla, Sachin Kumar & Garza-Reyes, Jose Arturo & Kazancoglu, Yigit, 2023. "Analysing the adoption barriers of low-carbon operations: A step forward for achieving net-zero emissions," Resources Policy, Elsevier, vol. 80(C).
    9. Stellingwerf, Helena M. & Groeneveld, Leendert H.C. & Laporte, Gilbert & Kanellopoulos, Argyris & Bloemhof, Jacqueline M. & Behdani, Behzad, 2021. "The quality-driven vehicle routing problem: Model and application to a case of cooperative logistics," International Journal of Production Economics, Elsevier, vol. 231(C).
    10. Soysal, Mehmet & Koç, Çağrı & Çimen, Mustafa & İbiş, Merve, 2023. "Managing returnable transport items in a vendor managed inventory system," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
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